Automatic detection of tb using soft computing techniques

Author(s)	Mr. KALAVALA HAREESH, Jimmy, Tjeng Wawan Cenggoro, Bens Pardamean
Country	India
Abstract	This study presents a novel approach for the automatic detection of tuberculosis (TB) using soft computing techniques, including artificial intelligence and machine learning. By leveraging medical imaging data such as chest X-rays, the method enhances traditional diagnostic methods through image preprocessing, feature extraction, and advanced classification algorithms like neural networks, fuzzy logic, and support vector machines. A labeled dataset is used to train and validate the models, significantly improving detection accuracy compared to conventional methods
Keywords	Keywords: Automatic detection, Tuberculosis (TB), Soft computing, Machine learning, Image processing, Chest X-rays, Early detection, Healthcare systems
Field	Engineering
Published In	Volume 7, Issue 2, March-April 2025
Published On	2025-04-08
DOI	https://doi.org/10.36948/ijfmr.2025.v07i02.40886
Short DOI	https://doi.org/g9fb6q

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International Journal For Multidisciplinary Research